P2P energy trading under unbalanced low-voltage distribution network constraints
Call Number: AIT Thesis no.ET-21-07 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. ET-21-07Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2021Description: 100 leaves : illSubject(s): Online resources: Dissertation note: Thesis (M. Eng.) - Asian Institute of Technology, 2021 Summary: Peer-to-peer (P2P) energy trading will be widely adopted in Thailand{u2019}s retail electricity market as a result of increase in global decarbonization, decentralized power systems, and the development of intelligent technologies, which will be sponsored by numerous renewable energy policies and programs. This study proposed a concept of P2P energy trading under network constraints among residential consumers and prosumers installing rooftop photovoltaics (PVs), which mainly focuses on low-voltage (LV) distribution systems. Three possible P2P models are investigated, namely community-based, full-P2P, and hybrid-P2P models. The market mechanism is well performed by using a double-sided auction method, integrating a consideration of network constraints, in which an unbalanced distribution system load flow (DLF) and strategies for the coordinated control of reactive power compensations and the active power curtailment of non-firm capacities were the well-mixed applications. Provincial Electricity Authority{u2019}s (PEA) Pattaya Smart Grid project with LV feeders is used as a case study to simulate different P2P models, which the simulation algorithm is developed by MATLAB software. The developed market mechanism provides P2P electricity prices with MCPs and the performance of eliminating the violations of voltages and loading of distribution transformers and lines; as a result, the compensated reactive energy and the curtailed active energy were absolutely equalized in all cases. The simulation results indicated that the full-P2P model is the preferred market model for the residential households, which provides the most amount of total clearing energy in P2P market. Thus, groups of prosumers and consumers can also gain the most benefit in the full-P2P model regarding the increase in financial profit and saving. It is interesting to note that PEA as a distribution system operator (DSO) and a retailer definitely lose their profit and cannot be fully compensated by wheeling fee in all P2P trading models due to losing a large amount of revenue from selling electricity to households.
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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy
Thesis (M. Eng.) - Asian Institute of Technology, 2021
Peer-to-peer (P2P) energy trading will be widely adopted in Thailand{u2019}s retail electricity market as a result of increase in global decarbonization, decentralized power systems, and the development of intelligent technologies, which will be sponsored by numerous renewable energy policies and programs. This study proposed a concept of P2P energy trading under network constraints among residential consumers and prosumers installing rooftop photovoltaics (PVs), which mainly focuses on low-voltage (LV) distribution systems. Three possible P2P models are investigated, namely community-based, full-P2P, and hybrid-P2P models. The market mechanism is well performed by using a double-sided auction method, integrating a consideration of network constraints, in which an unbalanced distribution system load flow (DLF) and strategies for the coordinated control of reactive power compensations and the active power curtailment of non-firm capacities were the well-mixed applications. Provincial Electricity Authority{u2019}s (PEA) Pattaya Smart Grid project with LV feeders is used as a case study to simulate different P2P models, which the simulation algorithm is developed by MATLAB software. The developed market mechanism provides P2P electricity prices with MCPs and the performance of eliminating the violations of voltages and loading of distribution transformers and lines; as a result, the compensated reactive energy and the curtailed active energy were absolutely equalized in all cases. The simulation results indicated that the full-P2P model is the preferred market model for the residential households, which provides the most amount of total clearing energy in P2P market. Thus, groups of prosumers and consumers can also gain the most benefit in the full-P2P model regarding the increase in financial profit and saving. It is interesting to note that PEA as a distribution system operator (DSO) and a retailer definitely lose their profit and cannot be fully compensated by wheeling fee in all P2P trading models due to losing a large amount of revenue from selling electricity to households.
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